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IEEE/IAS Conference on Industrial and Commercial power system Asia (IEEE I and CPS Asia)

作者： Huang, Shiying Yang, Ming Yun, Jiangyang Li, Peng Zhang, Qiang Xiang, Guangwei Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China Shandong Elect Power Dispatching & Control Ctr Jinan Peoples R China State Grid Corp China Heilongjiang Elect Power Co Harbin Peoples R China

ISBN: (纸本)9781665434980

This paper investigates the collaborative charging problem of plug-in hybrid electric vehicles (PHEVs) in a residential area charging station (CS) under an interaction mechanism. The target is to coordinate the charging strategies of all PHEVs to minimize charging cost of PHEVs on the one hand, and avoid the load peak of CS formed by charging behavior of PHEVs on the other hand. At the same time, the usage habits of PHEV owners, the uncertainty of time-varying electricity price in power market, and operation constraints of PHEVs and CS are also taken into account in this paper. To this end, this paper proposes a data-driven multi-agent PHEVs collaborative charging scheme based on deep reinforcement learning (DRL) method. Firstly, PHEVs are respectively constructed as agents. The interaction among PHEVs in the CS are formulated as a Markov Game. Then, a multi-agent PHEVs charging scheduling algorithm based on a multi-agent deep deterministic policy gradient (MADDPG) method is developed, in which each agent (i.e., PHEV) expects to minimize its cost by choosing the optimal charging strategy during the charging horizon. The proposed method can learn from data mining and gradually grasp the system operation rules by input and output data. Simulations are presented at last to validate the effectiveness of the proposed method.

关键词： charging strategy deep reinforcement learning interaction mechanism multi-agent system Plug-in hybrid electric vehicle (PHEV)

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Equivalence analysis of different sequence impedance modeling methods

Equivalence analysis of different sequence impedance modelin...

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China International Electrical and Energy Conference (CIEEC)

作者： Qiao Fang Facai Xing Zhe Jiang Yujing Zhao Cheng Wu Power Grid Technology Center State Grid Shandong Electric Power Research Institute Jinan China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China Shandong Electric Power Dispatching and Control Center State Grid Shandong Electric Power Company Jinan China

The sequence impedance has a clear physical meaning and can be directly measured by commercial equipment, so it is widely used for stability analysis in the field of electrical engineering. It can be transformed from dq impedance indirectly or calculated based on Harmonic State Space (HSS) theory directly. This paper analyzes the equivalence of the above two methods. Firstly, the dq impedance model of grid-connected converter is established, and the equivalence of impedance in dq domain and sequence domain is proved by mathematical transformation. Then, modified sequence impedance model of grid-connected converter is established considering the frequency coupling phenomenon. On the other hand, the impedance model can also be obtained from HSS modeling with h order harmonics. Subsequently, the relationship between the modified sequence impedance and HSS impedance can be found. The former is a special case when the latter takes h=2. When considering the coupling effect of higher harmonics, HSS impedance model has higher accuracy. Finally, the accuracy and the equivalence of the above-mentioned two methods are verified by frequency sweep.

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Photovoltaic power forecast based on satellite images considering effects of solar position

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APPLIED ENERGY 2021年 302卷 117514-117514页

作者： Si, Zhiyuan Yang, Ming Yu, Yixiao Ding, Tingting Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China

The rapid variation of clouds is the main factor that causes the fluctuation of photovoltaic power. (1)The satellite images contain plenty of information about clouds, applicable for photovoltaic power forecast. However, in practice, two main factors obstruct the application of the satellite images: 1) the relatively low update frequency of the satellite images mismatches the photovoltaic power forecasting frequency, and 2) the cloud region that blocks the sunlight changes significantly with time. In this paper, a novel satellite image-based approach for photovoltaic power forecast is proposed to overcome these obstacles and achieve accurate forecasting results. Firstly, concerning the hourly updated satellite images, a nonlinear cloud movement forecasting model, considering the thickness and shape changes of the cloud, is presented to forecast the hourly variation of the images. Secondly, an active cloud region selection rule is derived based on the changing solar position to dynamically select the cloud region that blocks the concerned photovoltaic power station in a satellite image. Thirdly, a sequential cloud region selection algorithm is provided to estimate the intra-hour variation of the cloud to match the photovoltaic power forecasting frequency. Finally, the photovoltaic power is predicted using the XGBoost algorithm concerning the effects of the cloud and other influencing factors. Testing results show that the proposed method can achieve more accurate photovoltaic power forecasts using the low update frequency satellite images. Meanwhile, the superior performance compared with other benchmarks also verifies the effectiveness of considering cloud information obtained by the proposed method for photovoltaic power forecast.

关键词： Cloud motion forecast Photovoltaic power forecast Satellite images Solar position XGBoost

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Application of Python Parallel Computing in Online Identification of Thevenin Equivalent Parameters

Application of Python Parallel Computing in Online Identific...

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3rd IEEE Student Conference on Electrical Machines and systems (SCEMS)

作者： Meng Xinyuan Wen Tao Ma Kaigang Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China

ISBN: (数字)9781728156224

ISBN: (纸本)9781728156224

The premise of analysing static voltage stability of large power grids online is identifying Thevenin equivalent parameters rapidly and accurately. And based on the current reaearch in this field, this paper analyses its formation mechanism and the feasibility of parallel programming in Python. The simulation test and analysis are carried out on the actual system. The results demonstrate that parallel programs can reduce the calculating time of Thevenin equivalent parameters significantly, make full use of computer performance and improve CPU utilization futher.

关键词： thevenin equivalent parameters python parallel programs

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Defect Analysis of power system Secondary Equipment Based on Cluster Analysis and Association Rule 8

Defect Analysis of Power System Secondary Equipment Based on...

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8th International Forum on Electrical Engineering and Automation (IFEEA)

作者： Zheng, Maoran Mu, Jinshuang Gao, Zhanjun Chen, Zhaohui Yu, Jiang Li, Zhenghong China Southern Power Grid Co Ltd Guangzhou 510623 Guangdong Peoples R China Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Shandong Peoples R China

ISBN: (纸本)9781665400886

In order to effectively improve the operation level of secondary equipment in the power system, based on the historical defect data of the secondary equipment, this paper takes the mining of the correlation between the secondary equipment defect data as the starting point, it proposes a method that combines cluster analysis and association analysis. First, this paper analyzes the basic ideas of cluster analysis and association analysis, then establishes the defect analysis model of the secondary equipment of this method. In the model, it uses cluster analysis to classify defect data firstly, clustering related defect data into a cluster, then uses association rules for further defect analysis. The result shows, this method can quickly and effectively dig out the correlation between defect data, able to further analyze the family defects of secondary equipment, it can provide certain guidance for equipment maintenance and daily operation.

关键词： Cluster analysis Association rules Familial defect Defect analysis

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Implementation of Vector Oriented control of DFIG based on FPGA 3

Implementation of Vector Oriented Control of DFIG based on F...

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3rd International Conference on power and Energy Applications, ICPEA 2020

作者： Wang, Zelin Zhao, Haoran Li, Bing Gao, Shuning Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan China

ISBN: (纸本)9781728190297

control strategy is indispensable in the use of doubly fed induction generator (DFIG). Vector oriented control (VOC) is a control strategy that has been tested by many scholars in DFIG on software. Field-Programmable Gate Array (FPGA), with the powerful capability of parallel computing and satisfying clocking frequency up to 200MHz, has widely applications in the high-speed data processing. Moreover, system Generator, as a tool developed by Xilinx, is a Simulink-based toolkit for FPGA developers. Thus, this paper implements VOC on FPGA by using system Generator. The simulation result shows that FPGA works well on VOC under the clocking frequency of 100MHz. This research solves the timing problem of loop design in system Generator and lays the foundation of real-time simulation of DFIG. © 2020 IEEE.

关键词： Software testing

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Transient Characteristics Analysis of Shunt Capacitor Asynchronous Energizing

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IEEE TRANSACTIONS ON power DELIVERY 2020年第5期35卷 2186-2195页

作者： Liang, Jiabi Zhu, Ke Shandong Univ Sch Elect Engn Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Shandong Peoples R China

The capacitor energizing transient as a kind of typical disturbance is used in the studies of power quality, condition monitoring, and other fields, and all studies heavily rely on transient characteristics. However, most characteristics are established based on the three-phase capacitor synchronous energizing (SE), and the effect of asynchronous energizing (AE) is neglected, which may affect the relevant studies. In this paper, the main characterizations of the capacitor AE transient, such as the oscillation frequency, time constant, and transient magnitude are analyzed considering the operation modes of the system and capacitor neutral points. The effect of the three-phase circuit asymmetry on the characterizations is investigated. The downstream voltage magnification phenomena in not only positive-sequence circuit but also zero-sequence circuit caused by the capacitor AE are also revealed. The theoretical analysis, computer simulation and lab experiment results have verified the effectiveness of the characteristics.

关键词： Capacitors Transient analysis Time-frequency analysis Integrated circuits Resistance Inductance Capacitor capacitor energizing transient characteristic synchronous asynchronous voltage magnification

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A Hybrid Photovoltaic power Prediction Model Based on Multi-source Data Fusion and Deep Learning

A Hybrid Photovoltaic Power Prediction Model Based on Multi-...

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3rd IEEE Student Conference on Electrical Machines and systems (SCEMS)

作者： Si, Zhiyuan Yang, Ming Yu, Yixiao Ding, Tingting Li, Menglin Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China

ISBN: (纸本)9781728156224

With the rapid development of the world economy, environmental and energy problems have become increasingly prominent. This fact motivates the exploitation of renewable energy, such as solar power. Solar photovoltaic (PV) power has been integrated into modern smart grids on a large scale. Accurate photovoltaic prediction is the key to ensure the stable operation of the power grid. The single prediction model is difficult to be universal due to the limitations of the model. Therefore, this paper proposes a hybrid ultra-short-term photovoltaic power prediction model based on multi-source data fusion and deep learning. First, the satellite cloud images, historical power sequences, and numerical weather prediction (NWP) data are fused. Then, the photovoltaic power prediction models are established by using appropriate deep learning methods (convolutional neural networks (CNN), long-short term memory (LSTM) networks, and Extreme Gradient Boosting (XGBoost)) according to different data. Finally, the three models are combined to get the final prediction result. The results show that the proposed method in this paper has better forecasting performance than other single models.

关键词： convolutional neural networks mapping model photovoltaic power forecasting satellite images XGBoost

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Reliability Evaluation of Distribution Grid Considering Flexible Grid Connection of Distributed Photovoltaic 2

Reliability Evaluation of Distribution Grid Considering Flex...

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2nd International Conference on Electronics, Communications and Information Technology, CECIT 2021

作者： Li, Zecheng Sun, Yanying Feng, Chen State Grid Ningxia Electric Power Research Institute Yinchuan China School of Mechanical Electronic and Information Engineering Beijing100083 China Shandong University The Key Laboratory of Power System Intelligent Dispatch and Control Jinan China

ISBN: (纸本)9781665437578

Aiming at the problem that the flexible access of distributed photovoltaics to the distribution network affects its reliability, this paper establishes a model of the distributed photovoltaic output probability based on the typical output characteristics of distributed photovoltaics firstly. Subsequently, the power grid risk assessment indicators are determined to facilitate the quantification of distribution network risks, including voltage over-limit, power over-limit, and load loss risk indicators. Finally, a distribution network model containing distributed photovoltaic grid-connected is established on the MATlab simulation platform, and the risk assessment of the distribution network containing distributed photovoltaic grid-connected is carried out. © 2021 IEEE.

关键词： Risk assessment

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Response-Driven Identification of Voltage Instability in AC/DC Hybrid Grid with New Energy

Response-Driven Identification of Voltage Instability in AC/...

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IEEE Asia power and Energy Engineering Conference (APEEC)

作者： Zewen Ding Zhuan Zhou Qichao Chen Fei Wang Junyu Liu Chongyang Dang Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education School of Electrical Engineering Shandong University Jinan China State Grid Xinjiang Electric Power CO. Ltd. Urumgi China State Grid Economic and Technological Research Institute CO. Ltd. Beijing China

ISBN: (数字)9798331517540

ISBN: (纸本)9798331517557

With the large-scale integration of new energy and the extensive operation of high-voltage direct current (HVDC) transmission projects, a variety of new transient voltage instability scenarios have emerged in the AC/DC hybrid grid with a high proportion of new energy. Traditional pre-planned strategies, which rely on predefined response tables to address different instability scenarios, are increasingly inadequate to effectively handle all instability situations. In response to this issue, this paper proposes a voltage instability identification method suitable for the AC/DC hybrid grid with new energy. Firstly, the various voltage instability scenarios existing in the AC/DC hybrid grid with new energy and their mechanisms are analyzed. Then, according to the characteristics of different instability scenarios, key response feature is extracted, and a method for identifying voltage instability scenarios is proposed. Finally, the AC/DC hybrid grid with a high proportion of new energy is modelled in BP A, different instability scenarios are simulated, and the proposed voltage instability identification method is verified to be able to effectively identify different voltage instability scenarios through simulation.

关键词： Electrical engineering HVDC transmission Asia Voltage High-voltage techniques Feature extraction Large scale integration Transient analysis

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